No coding required ... but

Over the last 12 months, my curiosity drove me to ride the Artificial Intelligence (AI)/Machine Learning (ML) train. I went from having basic coding knowledge to crafting Generative Adversarial Networks (GANs) and creating faces of people that don't exist.

Well ... after all, I had to find something entertaining to do during our multiple Aussie snap lockdowns!

Here's a sample of the faces generated by my GAN model ->

I must confess that I had little understanding of the fundamentals behind Artificial Intelligence, the difference between AI and ML, and not to mention why some people call it a "blackbox". All things considered, this made me realise the importance of data literacy and made me question :

what is holding back some people or businesses from becoming fully data-driven?

For those that are not familiar with the term, ‘data literacy’ is the ability to read and interpret data in order to draw inferences from it. At the very basic level, this means being able to understand where data comes from, how to analyse it and how to extract insights to aid the decision making process.

In the report from Qlik and The Data Literacy Project - The $500m Data Literacy Opportunity report - companies in Waste Management and Remed Services scored 81.1/100 in corporate data literacy, while the Healthcare and Social Assistance industry came last with a score of 67.1/100. Probably not what you would expect, right?

After some good ol' online reading, I found that the most common pitfalls are:

• Cultural challenges to accept change;
• Abrupt changes in the technology used;
• Poor scope on their data literacy program;
• Not enough leadership involvement; and
• Lack of common understanding on what data skills are needed per level.

I found this last point very true because more often than not, companies roll out amazing digital programs to upskill their workforce. However, without a shared understanding of what employees are supposed to do with their new data superpowers ... it will only be a matter of time until they start forgetting what they learned.

Think about it like planning the curriculum of someone that wants to learn a new language. Some people might want to learn Spanish to travel all around Latin America, while others just need to learn the magic words "una cerveza por favor" for that trip to a 5 star resort in the Caribbean.

While you don't need to learn how to become a full-stack developer, learning the fundamentals of coding or taking a short course on data analytics might help you bridge the gap between yourself and the developers in your company. And having a clear and collective understanding of your roles' responsibility on data will make your life easier.

On the flipside ... the OECD's report - Core Foundations for 2030 - highlights that cognitive foundations (literacy and numeracy) are constantly evolving as the world becomes more digitally enabled. Schools all around the world are starting to incorporate digital and data literacy into their programmes. Hopefully, we will start to see a trend of future generations speaking "data" as a second language.

Image credits: Top - Photo by?Photo by?Suad Kamardeen?on?Unsplash?